Chris Eliasmith

Professor
Royal Society of Canada, College of New Scholars
Canada Research Chair in Theoretical Neuroscience
Department of Philosophy
Department of Systems Design Engineering
University of Waterloo 
Waterloo, Ontario
N2L 3G1
Canada

email: celiasmith@uwaterloo.ca

[Education] [Books] [Refereed Journal Articles] [Refereed Conference Papers] [Chapters, Encyclopedia, etc.] [Edited Publications] [Awards] [Conferences] [Committees and Professional Affiliations]

Research Positions

2011-Present

Full Professor

Department of Philosophy
Department of Systems Design Engineering
Cheriton School of Computer Science (cross appointment)
University of Waterloo

2006-Present

Canada Research Chair in Theoretical Neuroscience (Tier II)

2007-Present

Director, Centre for Theoretical Neuroscience
University of Waterloo

2005-2011

Associate Professor

Department of Philosophy
Department of Systems Design Engineering
Cheriton School of Computer Science (cross appointment)
University of Waterloo

2001-2005

Assistant Professor

Department of Philosophy
University of Waterloo

2000-2001

Post-Doctoral Research Associate

Computational Neuroscience Research Group
McDonnell Center for Higher Brain Function
Washington University Medical School

Education

2008 - Present

Licensed Professional Engineer (Ontario)

1996 - 2000

Ph.D. in Philosophy
Philosophy-Neuroscience-Psychology Program
Washington University in St. Louis, St. Louis, MO, USA

Thesis: How neurons mean: A neurocomputational theory of representational content (pdf version)

Areas of Interest: Philosophy of Mind, Theoretical Neuroscience, Cognitive Science, Philosophy of Science (esp. Neuroscience), Epistemology

1994 - 1995

M.A. Philosophy
University of Waterloo, Waterloo, Ontario, Canada 

Thesis: Mind as a dynamic system (pdf)

1989 - 1994

B.A.Sc. Systems Design Engineering, First Class Honours
University of Waterloo, Waterloo, Ontario, Canada 

Books

Eliasmith, C. (2013) How to build a brain: A neural architecture for biological cognition. Oxford University Press. (Amazon link)

Eliasmith, C. and C. H. Anderson (2003). Neural Engineering: Computation, representation and dynamics in neurobiological systems. MIT Press. (Amazon.com).

Refereed Journal Articles

[Theoretical Neuroscience][Theoretical Psychology][Philosophy]

*Note: Many of these publications and related ones not listed can be found in full at my lab's main website.

Theoretical Neuroscience

Eliasmith, Chris and Oliver Trujillo. The use and abuse of large-scale brain models. Current Opinion in Neurobiology, 25:1-6, 2013. [online]

Rasmussen, Daniel and Chris Eliasmith. Modeling brain function: current developments and future prospects. JAMA Neurology, 70(10):1325-1329, 2013. [online]

Eliasmith, C., Stewart T. C., Choo X., Bekolay T., DeWolf T., Tang Y., Rasmussen, D. (2012). A large-scale model of the functioning brain. Science. 338(6111), 1202-1205. (reprint)

Stewart, T. C., Bekolay T., & Eliasmith C. (2012). Learning to select actions with spiking neurons in the basal ganglia. Frontiers in Decision Neuroscience. 6. (online)

DeWolf, T., & Eliasmith C. (2011). The neural optimal control hierarchy for motor control. The Journal of Neural Engineering. 8, 21. (online)

MacNeil, D., Eliasmith, C. (2011). Fine-tuning and the stability of recurrent neural networks. PLoS ONE. 6(9), 22885. (online)

Eliasmith, C., Martens, J. (2011). Normalization for probabilistic inference with neurons. Biological Cybernetics. 104(4), 251-262. (online)

Tripp B.P. and Eliasmith C. (2010) Population models of temporal differentiation. Neural Computation. 22(3):621-59 (.pdf penultimate version). 

Stewart, T.C., Tripp, B., Eliasmith, C. (2009) Python Scripting in the Nengo Simulator. Frontiers in Neuroinformatics. 3:7 (online).

Parisien, C., C. H. Anderson, and C. Eliasmith (2008). Solving the problem of negative synaptic weights in cortical models. Neural Computation. 20: 1473-1494 (pdf penultimate version).

Tripp, B. and C. Eliasmith (2007). Neural populations can induce reliable postsynaptic currents without observable spike rate changes or precise spike timing. Cerebral Cortex. 17:1830-1840 (on-line) (pdf penultimate version).

Singh, R. and C. Eliasmith (2006). Higher-dimensional neurons explain the tuning and dynamics of working memory cells. Journal of Neuroscience. 26: 3667-3678. (pdf version).

Kuo, D. and C. Eliasmith (2005) Integrating behavioral and neural data in a model of zebrafish network interaction. Biological Cybernetics. 93(3): 178-187 (pdf version - penultimate).

Eliasmith, C. (2005). A unified approach to building and controlling spiking attractor networks. Neural Computation. 17(6): 1276-1314 (pdf version - penultimate)

Conklin, J. and C. Eliasmith (2005). An attractor network model of path integration in the rat. Journal of Computational Neuroscience. 18: 183-203 (pdf version)

Theoretical psychology

Rasmussen, Daniel and Chris Eliasmith. God, the devil, and details: fleshing out the predictive processing framework. Behavioral and Brain Sciences, 36:223-224, 2013. [online]

Eliasmith, C. (2011). The complex systems approach: Rhetoric or revolution? Topics in Cognitive Science. doi: 10.1111/j.1756-8765.2011.01169.x (online)

Stewart, T., T. Bekolay, C. Eliasmith (2011). Neural representations of compositional structures: Representing and manipulating vector spaces with spiking neurons. Connection Science. 22(3), 145-153. (pdf)

Rasmussen, D. and C. Eliasmith (2011). A neural model of rule generation in inductive reasoning. Topics in Cognitive Science (TopICS) 3(1): 140-153. doi: 10.1111/j.1756-8765.2010.01127.x (online)

Stewart, T. C., Y. Tang, and C. Eliasmith (2011) A biologically realistic cleanup memory: Autoassociation in spiking neurons. Cognitive Systems Research, 12, 84-92. (pdf)

Litt, A, C. Eliasmith, and P. Thagard (2008) Neural affective decision theory: Choices, brains, and emotions. Cognitive Systems Research. 9:252-273 (pdf penultimate version).

Eliasmith, C. and P. Thagard (2001). Integrating structure and meaning: A distributed model of analogical mapping. Cognitive Science. (html version)

Philosophy

Eliasmith, C. (2010). How we ought to understand computation in the brain. Studies in History and Philosophy of Science. 41(3) 131-320 (pdf penultimate version).

Eliasmith, C. (2007). How to build a brain: From function to implementation. Synthese. 153(3): 373-388 (pdf penultimate version).

Litt, A. C. Eliasmith, F. Kroon, S. Weinstein and P. Thagard (2006). Is the brain a quantum computer? Cognitive Science. 30(3): 593-603 (pdf version).

Eliasmith, C. (2005). A new perspective on representational problems. Journal of Cognitive Science. 6: 97-123. (pdf version - penultimate).

Eliasmith, C. (2003). Moving beyond metaphors: Understanding the mind for what it is. Journal of Philosophy. C(10):493-520. Reprinted in Brooks and Akins (eds). Cognition and the Brain. 2005. Cambridge University Press. p.131-159. (pdf version)

Eliasmith, C. (2002). The myth of the Turing machine: The failings of functionalism and related theses. Journal of Experimental and Theoretical Artificial Intelligence. 14: 1-8. (html version)

Eliasmith, C. (2002). Discreteness and relevance: A reply to Roman Poznanski. Minds and Machines. 12: 437-438. (pdf version)

Eliasmith, C. (2001). Attractive and in-discrete: A critique of two putative virtues of the dynamicist theory of mind. Minds and Machines. 11: 417-426. (html version)

Eliasmith, C. (2000) Is the brain analog or digital?: The solution and its consequences for cognitive science. Cognitive Science Quarterly. 1(2): 147-170. (html version).

Eliasmith, C. (1997). Computation and dynamical models of mind. Minds and Machines, 7, 531-541. (html version)

Eliasmith, C. and P. Thagard (1997). Waves, particles, and explanatory coherence. British Journal of the Philosophy of Science, 48, 1-19. (html version)

Eliasmith, C. (1996). The third contender: A critical examination of the dynamicist theory of cognition. Philosophical Psychology, 9, 441-463. Reprinted in P. Thagard (Ed.). (1998). Mind readings: Introductory selections in cognitive science. MIT Press. (html version)

Refereed Conference Papers

[Theoretical Neuroscience] [Theoretical Psychology] [Machine Intelligence][Philosophy]

Theoretical Neuroscience

Eric Hunsberger, Matthew Scott, and Chris Eliasmith. Heterogeneity increases information transmission in neuronal populations. COSYNE, 2013. [online]

Daniel Rasmussen and Chris Eliasmith. A neural reinforcement learning model for tasks with unknown time delays. In Cognitive Science Society, 3257-3262. 2013. [online]

Sergio Davies, Terrence C. Stewart, Chris Eliasmith, and Steve Furber. Spike-based learning of transfer functions with the SpiNNaker neuromimetic simulator. International Joint Conference on Neural Networks, 2013. [online]

Galluppi, F., Davies S., Stewart T., Eliasmith C., & Furber S. (2012). Real Time On-Chip Implementation of Dynamical Systems with Spiking Neurons. IJCNN. (online)

Dethier, J., Nuyujukian, P., Eliasmith, C., Stewart, T., Elassaad, S.A., Shenoy, K., Boahen, K.
(2011). A brain-machine interface operating with a real-time spiking neural network control
algorithm. Neural Information Processing Systems (NIPS). [online]

Travis Dewolf & C. Eliasmith (2011). Applying optimal hierarchical controllers to neural models of motor control. International Conference on Applied Mathematics, Modeling and Computational Science (AMMCS).

Trevor Bekolay (2011). A general error-modulated STDP learning rule applied to reinforcement learning in the basal ganglia. CoSyne 2011. Salt Lake City, Utah. [online]

B. Bobier, T. Stewart. & C. Eliasmith. (2011) The Attentional Routing Circuit: Receptive Field Modulation Through Nonlinear Dendritic Interactions. CoSyne 2011. Salt Lake City, Utah. [online]

Travis Dewolf & C. Eliasmith A spiking neuron model of movement and pre-movement activity in M1. CoSyne 2011. Salt Lake City, Utah. [online]

A neuronal mechanism for linking actions to outcomes in the medial prefrontal cortex. Cosyne 2011, Salt Lake City, B. Liu, M. Caetano, N. Narayanan, C. Eliasmith, and M. Laubach.

Stewart, T.C., Choo, X. & C. Eliasmith (2010) Dynamic Behaviour of a Spiking Model of Action Selection in the Basal Ganglia. 10th International Conference on Cognitive Modeling. Aug 2010. [online]

Travis Dewolf & C. Eliasmith (2010) NOCH: A framework for biologically plausible models of neural motor control. Neural Control of Movement 20th Annual Conference. Naples, FL. June 2010. [online]

B. Bobier, T. Stewart. & C. Eliasmith. (2010) Dynamic Routing Model for Visuospatial Attention.  Cosyne. Salt Lake City. [online]

Bryan Tripp & C. Eliasmith (2008) Plasticity and population coding. COSYNE. Salt Lake City, Feb. 2008.

Bryan Tripp & C. Eliasmith (2007) Population coding in the basal ganglia. International Basal Ganglia Society IX, Amsterdam, ND, Sept.

James Martens & C. Eliasmith (2007). A neurologically plausible implementation of statistical inference applied to random dot motion. Computational Neuroscience (CNS*07), Toronto, July.

Bryan Tripp & C. Eliasmith (2007) Supervision of motor cortex by basal ganglia. Computational Neuroscience (CNS*07), Toronto, July.

Abninder Litt, Paul Thagard & C. Eliasmith (2007) A large-scale neurocomputational model of emotional decision making. Computational Neuroscience (CNS*07), Toronto, July.

Bryan Tripp & C. Eliasmith (2007) Temporal coding of continuously-varying inputs. Computational Neuroscience (CNS*07), Toronto, July.

Bryan Tripp & C. Eliasmith (2006) Comparison of neural circuits that estimate temporal derivatives. COSYNE '06, Salt Lake City, Mar.

Parisien, C., C. H. Anderson & Eliasmith, C. (2006). Biologically realistic neural inhibition in arbitrary neural circuits. COSYNE '06, Salt Lake City, Mar. chosen for highlight talk.

R. Singh & C. Eliasmith (2004) A dynamic model of working memory in the PFC during a somatosensory discrimination task. COSYNE 04, Cold Spring Harbor Labratory. Mar.

Kuo, D. and C. Eliasmith (2004). Understanding interactions between networks controlling distinct behaviors: Escape and swimming in larval zebrafish. Neurocomputing. 58-60: 541-547. (pdf version)

C. Eliasmith (2003) A general framework for large-scale simulations applied to working memory. ICCNS'03, Boston, MA. May

Eliasmith, C., M. B. Westover, and C. H. Anderson (2002). A general framework for neurobiological modeling: An application to the vestibular system. Neurocomputing. 46: 1071-1076. (pdf version).

M. B. Westover, C. Eliasmith and C. H. Anderson C. Eliasmith (2002). Linearly decodable functions from neural population codes. Neurocomputing. 45: 691-696. (pdf version)

Eliasmith, C. and C. H. Anderson (2001). Beyond bumps: Spiking networks that store smooth n-dimensional functions. Neurocomputing. 38, 581-586. (pdf version)

C. Eliasmith (2001) A general framework for neurobiological modeling: An application to the vestibular system. Computational Neuroscience (CNS*2001). Monterey, CA. July.

Eliasmith, C. and C. H. Anderson (2000). Rethinking central pattern generators: A general framework. Neurocomputing. 32-33(1-4): 735-740 (pdf version)

C. Eliasmith (2000) Beyond bumps: Spiking networks that store smooth n-dimensional functions. Computational Neuroscience (CNS *2000). Brugge, Belgium. July.

Eliasmith, C. and C. H. Anderson (1999). Developing and applying a toolkit from a general neurocomputational framework. Neurocomputing, 26(1): 1013-1018 (pdf version)

C. Eliasmith (1999) Rethinking central pattern generators: A general framework. Computational Neuroscience (CNS *99). Pittsburgh, PA. July.

Theoretical Psychology

Eric Crawford, Matthew Gingerich, and Chris Eliasmith. Biologically plausible, human-scale knowledge representation. Cognitive Science Society, 412-417. 2013. [online]

Trevor Bekolay, Carter Kolbeck, and Chris Eliasmith. Simultaneous unsupervised and supervised learning of cognitive functions in biologically plausible spiking neural networks. In Cognitive Science Society, 169-174, 2013. [online]

Carter Kolbeck, Trevor Bekolay, and Chris Eliasmith. A biologically plausible spiking neuron model of fear conditioning. In International Conference on Cognitive Modeling, 53-58, 2013. [online]

Eric Hunsberger, Peter Blouw, James Bergstra, and Chris Eliasmith. A neural model of human image categorization. Cognitive Science Society, 633-638, 2013. [online]

Peter Blouw and Chris Eliasmith. A neurally plausible encoding of word order information into a semantic vector space. In Cognitive Science Society, 1905-1910. 2013. [online]

Travis DeWolf and Chris Eliasmith. A neural model of the development of expertise. The 12th International Conference on Cognitive Modelling, 2013. [online]

Xuan Choo and Chris Eliasmith. General instruction following in a large-scale biologically plausible brain model. In Cognitive Science Society, 322-327, 2013. [online]

Terrence C. Stewart and Chris Eliasmith. Parsing sequentially presented commands in a large-scale biologically realistic brain model. In Cognitive Science Society, 3460-3467, 2013. [online]

Aziz Hurzook, Oliver Trujillo, and Chris Eliasmith. Visual motion processing and perceptual decision making. In Cognitive Science Society, 2590-2595, 2013. [online]

Terry Stewart & C. Eliasmith (2011) Neural Cognitive Modelling: A Biologically Constrained Spiking Neuron Model of the Tower of Hanoi Task. (Carlson, L., Hölscher C., & Shipley T., Ed.). 33rd Annual Conference of the Cognitive Science Society. [online]

Stewart, T.C., Choo, X. & C. Eliasmith (2010) Symbolic Reasoning in Spiking Neurons: A Model of the Cortex/Basal Ganglia/Thalamus Loop. 32nd Annual Meeting of the Cognitive Science Society. Aug. 2010. [online]

Choo, X. & C. Eliasmith (2010) A Spiking Neuron Model of Serial-Order Recall. In Richard Cattrambone & Stellan Ohlsson (Eds.), 32nd Annual Conference of the Cognitive Science Society. Portland, OR: Cognitive Science Society. Aug 2010. [online]

Rasmussen, D. & C. Eliasmith (2010). A neural model of rule generation in inductive reasoning. In Richard Cattrambone & Stellan Ohlsson (Eds.), 32nd Annual Conference of the Cognitive Science Society. Portland, OR: Cognitive Science Society. Won Best Paper Award. [online]

Terrence C. Stewart & C. Eliasmith (2008) Building production systems with realistic spiking neurons. Cognitive Science Conference. Washington, DC. August. [online]

Abninder Litt, Paul Thagard & C. Eliasmith (2006) When matter matters: understanding brains to enrich behavioral explanations of judgments and decisions Society for Judgment and Decision Making. Houston, Nov.

Abninder Litt, Paul Thagard & C. Eliasmith (2006) Emotions shape decisions -- but how? A neurocomputational account Computational Cognitive Neuroscience Conference, Houston, Nov.

C. Eliasmith (2005) BioSLIE: Context-sensitive Linguistic Inference in a Biologically Realistic Simulation. Computational Cognitive Neuroscience Meeting. Washington DC : Nov.

C. Eliasmith (2005) Cognition with neurons: A large-scale, biologically realistic model of the Wason task. Cognitive Science Society Conference. Stresa , Italy : July

C. Eliasmith (2004) Learning context sensitive inference in a neurobiological simulation. AAAI Fall Symposium on Compositional Connectionism. Oct.

C. Eliasmith (2004) A neurobiological simulation of deductive reasoning. COSYNE 04, Cold Spring Harbor Labratory. Mar.

Eliasmith, C. (2004). Learning context sensitive logical inference in a neurobiological simulation. in Levy, S. and Gayler, R. (eds.). Compositional Connectionism in Cognitive Science. AAAI Fall Symposium. AAAI Press. p. 17-20. (pdf version).

Machine Intelligence

Tang, Y., Eliasmith, C. (2010). Deep networks for robust visual recognition. International Conference on Machine Learning. (pdf)

Carrilo et al. (2010) Concept Based Representations for Ranking in Geographic Information Retrieval. IceTAL 2010 7th International Conference on Natural Language Processing.

Carrillo, M.,  E. Villatoro-Tello, A. Lopez-Lopez, C. Eliasmith, M. Montes-y-Gomez and L. Villasenor-Pineda (2009) “Concept representations in Geographic Information Retrieval as Re-ranking Strategies” in 18th ACM Conference on Information and Knowledge Management. (pdf version)

Carrillo, M., C. Eliasmith , and A. Lopez-Lopez (2009) “Combining Text Vector Representations for Information Retrieval” in V. Matousek, P. Mautner (eds) Text, Speech and Dialogue. Proceedings of the 12th International Conference TSD 2009. (pdf version)

Carrillo, M., Villatoro-Tello, E., Lopez-Lopez, A., Eliasmith, C., Montes-y-Gomez, M., Villasenor-Pineda, L. (2009). Representing Context Information for Document Retrieval. In T. Andreasen et al. (Ed.), Flexible Query Answering Systems, FQAS 2009. 239-250. (pdf version)

Fishbein, J and C. Eliasmith (2008) Methods for augmenting semantic models with structural information for text classification. Advances in Information Retrieval. Springer. pp. 575-579. DOI 10.1007/978-3-540-78646-7_58 (online version)

Fishbein, J and C. Eliasmith (2008) Integrating structure and meaning: A new method for encoding structure for text classification. Advances in Information Retrieval. Springer. pp. 514-521.(online version)

Jon Fishbein & C. Eliasmith (2007) A new method for encoding structure for text classification. MMKD 2007, Waterloo, Oct. won best poster award.

Philosophy

C. Eliasmith (2000) The myth of the Turing machine: The failings of functionalism and related theses. American Philosophical Association, Central Division. Chicago, IL. April.

C. Eliasmith (1998) Attractive and in-discrete: A critique of two putative virtues of the dynamicist theory of mind. Society for Philosophy and Psychology. June, 1998. Poster. Southern Society for Philosophy and Psychology. April.

C. Eliasmith (1997) Structure without symbols: Providing a distributed account of high-level cognition. Southern Society for Philosophy and Psychology. March. (html version)

Chapters, Reviews, Encyclopedia, etc. (chronological)

Stewart, T. and C. Eliasmith. (2011) Compositionality and biologically plausible models. In W. Hinzen, E. Machery, and M. Werning (eds.) Oxford Handbook of Compositionality. Oxford University Press. (pdf penultimate version)

Eliasmith, C. (2009). Neurocomputational models: Theory and applications. In J. Bickle (Eds.) Oxford Handbook of Philosophy of Neuroscience. Oxford University Press. pp. 346-369 (pdf penultimate version).

Eliasmith, C. (2009). Dynamics, control, and cognition. In P. Robbins and M. Aydede (Eds.) Cambridge Handbook of Situated Cognition. Cambridge University Press. pp. 134-154 (pdf version)

Stewart, T. C., Tripp, B., & Eliasmith, C. (2008). Supplementing Neural Modelling with ACT-R. Proceedings of the 15th Annual ACT-R Workshop, Pittsburgh, USA.

Eliasmith, C. (2008) Review of The great brain debate: Nature or nurture? by John E. Dowling. The Quarterly Review of Biology. 83(2):210-211 (pdf penultimate version)

Stewart, T. C. & Eliasmith, C. (2008). Implementing the ACT-R Production System in Spiking Neurons. Proceedings of the 15th Annual ACT-R Workshop, Pittsburgh, USA.

Chris Eliasmith (2007) Attractor network. Scholarpedia 2(10):1380.

Eliasmith, C. (2007). Computational neuroscience. In P. Thagard (ed.), Philosophy of Psychology and Cognitive Science. Handbook of Philosophy of Science (Vol. 4). Amsterdam: Elsevier. (pdf version)

Eliasmith, C. (2006). Neurosemantics and categories. In C. Lefebvre and H. Cohen (eds.). Handbook of Categorization in Cognitive Science. Amsterdam: Elsevier. (pdf version)

Eliasmith, C. (2005). Cognition with neurons: A large-scale, biologically realistic model of the Wason task. In G. Bara, L. Barsalou, and M. Bucciarelli (Eds)., Proceedings of the 27 th Annual Meeting of the Cognitive Science Society. Stresa , Italy (pdf version).

Eliasmith, C. (2005). Large-scale neural modeling. In J. Wooley and H. Lin (eds.). Catalyzing Inquiry at the Interface of Computing and Biology. Washington: The National Academies Press. 173-178.

Eliasmith, C. (2003). Neural engineering: Unraveling the comlexities of neural systems. IEEE Canadian Review (43): 13-15. (pdf version).

Eliasmith, C. and W. Bechtel (2003). Symbolic vs. subsymbolic. In Lynn Nadel (Ed.), Encyclopedia of Cognitve Science. MacMillian.

Clark, A. and C. Eliasmith (2002). Philosophical issues in brain theory and connectionism. In M. Arbib (Ed.), Handbook of brain theory and neural networks (2nd ed.). Cambridge, MA: MIT Press. pp. 886-888. (html version)

Thagard, P., C. Eliasmith, P. Rusnock, and C. Shelley (2002). Epistemic coherence. In R. Elio (Ed.), Common sense, reasoning, and rationality. Vancouver Studies in Cognitive Science (Vol. 11). Oxford University Press. pp. 104-131. (html version)

Eliasmith, C. (1999). Review of C. Dilworth's The metaphysics of science: An account of modern science in terms of principles, laws, and theories. Dialogue, 37, 656-8. (html version )

Eliasmith, C. (1998). Dynamical models and van Gelder's dynamicism: Two different things. Commentary on van Gelder, T. (1998). The dynamical hypothesis in cognitive science. Behavioral and Brain Sciences, 21, 616-665. (html version)

Eliasmith, C. (1998). Review of William Lyons' Modern philosophy of mind. Philosophical Psychology, 11, 3.(html version)

Edited Publications

Eliasmith, C. (Ed.) (1998). Dictionary of philosophy of mind. Department of Philosophy, University of Waterloo. http://philosophy.uwaterloo.ca/MindDict/.

Awards/Grants

2014

Royal Society of Canada, College of New Scholars

2013-2016

EOARD of the AFOSR: A neural information field approach to computational cognition (with Dimitri Pinotsis)

2013-2018

ONR: Neuromorphics: Programmable analog computation through probabilistic digital communication (with Kwabena Boahen, Rajit Manohar)

2011-2016

CFI/OIT Leader's Opportunity Fund

2010-2015

NSERC Discovery Grant

2011-2012

NSERC Engage Grant

2008-2010

SHARCNET postdoctoral fellowship

2007

SHARCNET undergraduate funding fellowship

2007-2012

Leader's Opportunity Fund (CFI/OIT)

2006-

Canada Research Chair (Tier II) in Theoretical Neuroscience

2006-2011

National Sciences and Engineering Research Council Co-operative Research and Development (Matches OpenText)

2006-2011

OpenText Corp

2005-2010

National Sciences and Engineering Research Council Discovery Grant

2003-2005

National Sciences and Engineering Research Council Discovery Grant (see here)

2003-2008

Canadian Foundation for Innovation New Opportunities / Ontario Innovation Trust Grant (see here)

2000 - 2005

McDonnell Project Grant for Philosophy and the Neurosciences (see here)

1997 - 2000

Social Sciences and Humanities Research Council (SSHRC) Canada Doctoral Grant

1996 - 2001

McDonnell Foundation Fellowship for Philosophy-Neuroscience-Psychology Program

Selected Talks, Tutorials, Workshops, etc.

How to build a brain. McMaster University Neuroscience Colloqium, 2013. Invited talk.

How to build a brain. University of Michigan Psychology Colloqium, 2013. Invited talk.

From single neurons to cognition. Janelia Farms Colloqium, 2013. Invited talk.

Computation for a brain. Google Waterloo, 2013. Invited talk.

Building a brain: From single neurons to cognition. AAAI Symposium on Integrated Cognition, 2013. Keynote.

Neural engineering. Neural Engineering Transformative Technologies Summer School, 2013. Keynote talk and tutorial.

How to build a brain. Society for Computers in Psychology, 2013. Keynote talk.

Large-scale neural modeling. Stanford University MBC Colloqium, 2013. Invited talk.

How to build a brain. International Conference on Cognitive Modeling, 2013. Keynote talk.

From single cells to cognition. CIFAR Summer School, Toronto, 2013. Invited tutorial and talk.

How to build a brain. TEDxWaterloo, 2013. Invited talk. [youtube]

Integrative models of cognition. Cognitive Science Society Symposium, Berlin, 2013. Invited talk.

How to build a brain. University of Indiana Cognitive Science Seminar, 2013. Invited talk.

Can we build intelligent machines? Research Matters, McMaster University, 2013. Invited talk. [youtube]

Marr's Attacks: A gentle reminder. Marr Symposium on Levels of Description. Peebles and Cooper (organizers). Cognitive Science Society, 2012. Invited.

Integrating perception, action, and cognition in neuromorphic hardware and software. Led 3-week session. Telluride Neuromorphic Cognition Workshop. 2012. with Kwabena Boahen, Bryan Tripp, Terry Stewart (submitted proposal).

Function and form: Both matter for neural modelling. ASIC, 2012. Sardinia. Submitted talk.

Constructing a large-scale, nonlinear dynamical brain. Workshop on Nonlinear Dynamics in Complex Neural Architectures. Lyons, 2012. Invited talk.

Methods for large-scale functional modeling in neural hardware. ETHZ Zurich. 2012. Invited talk.

How to build a brain: From single cells to cognition. Coast to Coast Seminar Series. Waterloo (broadcast through Compute Canada), 2012 (slides). Invited talk.

From single cells to cognition in hardware and software. Led 3-week session. Telluride Neuromorphic Cognition Workshop. 2011. with Kwabena Boahen, Terry Stewart (submitted proposal).

How to build a brain: From single cells to cognitive systems. Rensselaer Polytechnic Institute. New York. 2011 Invited talk.

Neural-symbolic integration. 4.5h of lecture. Spring School on Interdisciplinary Cognitive Science. Meunster, Germany. 2011. Invited talks.

Large-scale neuro-cognitive modelling. One-day workshop. Cognitive Science. Boston. 2011.with Terry Stewart (submitted proposal).

Making brain dynamics useful: From single cells to cognition. Cosyne 2011 Workshops. Invited talk.

Neural circuits for persistent activity in medial prefrontal cortex. Society for Neuroscience. (poster 200.18). Nov 2010. Laubach, M., Caetano, M. S., Liu, B., Smith, N. J., Narayanan, N. S., & Eliasmith, C.

Rapid large-scale model construction: A application to working memory. John B. Pierce Lab, Yale University. Nov 2010, Invited talk.

A new learning rule for neural integrators. Cosyne Workshop on Persistent Activity. Feb, 2010. Invited talk.

Large-scale cognitive modelling. Neurocognitive Networks Workshop. Florida Atlantic. Feb. 2010. Invited talk.

Nengo: A new large-scale neural simulator. NIPS Demo, Dec. 2009.

MCMC with spiking neurons with Lloyd Elliott (first). NIPS 2009 Workshop on Bounded-rational analyses of human cognition: Bayesian models, approximate inference, and the brain.

How to build a brain. University of Montreal. Sept 2009. Invited talk.

Lage-scale cognitive modelling with spiking neurons. UQAM. Sept 2009. Invited talk.

Cognitive modelling with the NEF. Full day workshop ICCM, Aug. 2009.

Spiking attractor networks in the NEF. Columbia University. CTN Jan. 2009. Invited talk.

How to build a brain: A suggestion for how to unify the brain sciences. Perimeter Institute, Waterloo. October, 2008. invited talk.

Beyond representation: A general, unified method for characterizing neural computation over space and time. Bernstein Centre for Computational Neuroscience, Munich. May, 2008. invited talk.

How we ought to understand computation in the brain. Computation in Cognitive Science Workshop. July, 2008. Kings College, Cambridge. invited talk.

How to build a brain. Cognitive Science Seminar Series, York University, Nov, 2007. invited talk.

Modelling the mind: Unifying the new brain sciences. Annual Arts Public Lecture, University of Waterloo, Nov. 2007. invited talk.

Minds and brains through mathematics:
Theoretical neuroscience and mental representation
. British Society for Philosophy of Science. Bristol, UK, July 2007, invited keynote.

Large-scale models of neural computation, Unconventional Computation: Quo Vadis? Santa Fe Institute, March 2007, invited talk.

A biologically realistic model of statistical inference applied to random dot motion. COSYNE, Salt Lake City, February, 2007, with James Martens (1st), submitted poster.

Challenges for biological bayes:
Solving normalization
. COSYNE Workshop on Statistical Inference in the Brain, February, 2007, with James Martens (2nd), contributed talk.

Situated cognition: What's worth keeping? Frankfurt Institute for Advanced Studies (FIAS): Mind Group Symposium. Frankfurt, Germany, Oct. 2006. Invited keynote.

How to build a brain. IEEE Engineering in Medicine and Biology Society (EMBS), Waterloo, Oct. 2006. Invited demo.

Large-scale models of neural computation. Mind & Brain V: Physics and the Brain, Dubrovnik, Croatia, Oct. 2006. Invited talk.

Basics of computational modeling of brain function. Cognitive Systems:
Bridging Cellular to Social. Sandia National Labs, Santa Fe, June, 2006. Invited tutorial.

Classifying and evaluating theories and models
in theoretical neuroscience
. Models and Prediction
in Science, Science Studies, and Public Policy, UCSD, San Diego, May, 2006. Invited talk.

PCs, primates and people: Differences in kind or degree? UTism Conference on Cognitive Science. Toronto, Mar. 2006. Invited talk.

The biological plausibility and cognitive relevance of predictive coding. Predictive Coding Workshop. Aarhus University, Denmark, Feb. 2006. Invited talk.

A generalization of central pattern generators. Program No. 753.17. Washington, DC: Society for Neuroscience, 2005 with Bryan Tripp (1st). Contributed poster.

A computational model of the effects of prism adaptation in spatial neglect Program No. 287.15. Washington, DC: Society for Neuroscience, 2005 with Michael Lerman (1st) and James Danckert (2nd). Contributed poster.

From single cells to cognition: General methods and specific models. RIKEN Brain Sciences Institute. Wako City , Japan : Aug. 2005. Invited talk.

Dynamics in neural systems. McDonnell Project in Philosophy and Neuroscience. Caltech: June 2005. Invited talk

Neural engineering: Large-scale neurobiological simulations with applications. Research Colloquium in the School of Informatics, University of Edinburgh. Jun. 2004. Invited talk.

Neurosemantics and misrepresentation. Philosophy-Neuroscience-Psychology Colloquium. Washington University in St. Louis. Oct. 2003. Invited talk.

Beyond a metaphor: Understanding the mind for what it is. Philosophy Department Colloquium. Washington University in St. Louis. Oct. 2003. Invited talk.

Inference and prediction in neocortical circuits. American Institute of Mathematics, Palo Alto, CA. Sept. 2003. Invited workshop participant.

A neurosemantics for categories. Cognitive Science Summer School, University of Quebec at Montreal, Montreal, PQ. July, 2003. Invited talk.

Neurosemantics and misrepresentation. McDonnell Project in Philosophy and the Neurosciences, Heron Island, Australia. July, 2003. Invited talk.

A general framework for constructing large-scale, biologically plausible simulations. CNS *2003, Alicante, Spain. Jun. 2003. Submitted poster and 1/2 day workshop.

Neural engineering:
How to build large-scale, biologically plausible simulations of neural systems
. Mathematical Biosciences Institute, Ohio State University. Feb. 2003. Invited talk.

Beyond a metaphor: Understanding the mind for what it is. Philosophy Department Colloquium. University of Western Ontario. Oct. 2002. Invited talk.

Beyond metaphors: Computation, representation and dynamics in cognitive systems. Neuroscience and Philosophy. Carleton University. Oct. 2002. Invited talk.

A general framework for understanding neurobiological systems: An application to working memory. Center for Neuroscience, UC Davis. Apr. 2002. Invited talk.

Beyond a metaphor: Understanding the mind for what it is. Cognitive Science in the New Millennium Foundations, Directions, Applications, and Problems. CalState University, Long Beach. Apr. 2002. Invited talk.

Integrating representations, transformations, and dynamics: A general framework for understanding neurobiological systems. Caltech and Pitzer College, CA. Nov. 2001. Invited talk.

How brains represent: Sensing motion. University of Waterloo Cognitive Science Forum. June, 2001. Invited talk.

A general framework for simulating neurobiological networks applied to the vestibular system. Washington University Computational Neuroscience Series. April, 2001. Invited talk.

A change in perspective for philosophers, neuroscientists, and psychologists: A new take on representational problems. Washington University, Philosophy-Neuroscience-Psychology program work-in-progress colloquia. April, 1999. Volunteered talk.

Attractors, representation, and a neurocomputational framework. Computational Neuroscience (CNS *98). Santa Barbara, CA. July, 1998. Poster. Washington University Neuroscience Retreat. Potosi, MO. October, 1998. Invited talk.

The neural integrator: An application of the PDF modeling framework. Washington University Neuroscience Retreat. Potosi, MO. October, 1997. Poster.

Integrating structure and meaning: A distributed model of analogical mapping. Washington University, Philosophy-Neuroscience-Psychology program work-in-progress colloquia. October, 1996. Volunteered talk.

Committees, Professional Affiliations, and other activities

2009 -

Editorial board of Journal of Mind Theory

2007 -

Panel Expert for European Union IST Call for Cognitive Systems Proposals

2007

Organizer of COSYNE workshop on Statistical Inference

2006 -

Director, Centre for Theoretical Neuroscience

2005

Panel Expert for European Union IST Call for Cognitive Systems Proposals

2005 -

Neuroscience Society member

2004 -

Technical Advisory Board for Biomimetic Connections, Inc.

2004

National Science Foundation (NSF) Grant Panel for Collaborative Research in Computational Neuroscience

2004

Organizing Committee of AAAI Symposium: Connectionist Compositionality in Cognitive Science (Fall)

2004

Organizer of a workshop on Cultural Biology (May 21-23, University of Waterloo)

2002 -

University of Waterloo Cognitive Science Program Advisory Board

1998 -

Society for Philosophy and Psychology

1997 -

American Philosophical Association

1997 -

Canadian Philosophical Association

1997 -

Philosophy of Science Association

1997 -

Southern Society for Philosophy and Psychology